Sense signals and events
Observe business state and external change, initiating or adapting work when authorized conditions emerge.
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GEA OS
Long-Horizon Agent Runtime
Keep work moving toward long-horizon goals and outcomes.
Continuously sense enterprise and external signals, manage goals, plans, and durable state across interactions and workflows, and adapt the next action to intermediate results. Through the Harness, the runtime uses context, skills, and tools so work can pause, resume, and retry while remaining under human oversight and enterprise boundaries.
How It Works
Keep goals continuous across interactions and systems.
The long-horizon runtime extends a conversation into sustained execution: sensing change, initiating work, preserving state, and using the Harness to access context, skills, models, and tools.
Preserve sessions and state
Use events and checkpoints to preserve goals, plans, dependencies, and intermediate outcomes so work can pause and resume across time.
Execute through the Harness
Assemble context for the current step, route models, skills, and tools, and record inputs, outputs, and state changes for each call.
Recovery and escalation
Replan from intermediate outcomes, distinguish safe retry from compensation, and bring people in at low-confidence or high-risk moments.
Technical Artifact · Long-Horizon Operation
How a long-horizon objectivekeeps moving through change.
The five business scenarios share one long-horizon operating mechanism. In each enterprise, Tezign builds a dedicated long-horizon agent around its objectives, Context, systems, and accountability boundaries rather than applying a fixed workflow.
01
Current state
Maintain direction · Durable objective
Keep product opportunities and R&D constraints alive across cycles
Opportunity hypotheses, prior choices, R&D constraints, and experiment results persist across cycles.
Opportunity hypothesesR&D constraintsExperiment memory
Current outcome / Next action
Re-evaluate the direction when cost and user feedback change
Validation & Guardrails
Long-running work requires explicit state, failure, and stopping semantics.
Reliable operation goes beyond retry. It depends on where state is checkpointed, whether external actions can be replayed safely, how sandboxes isolate execution, and when work must stop and return to people.
How We Measure
01
Long-task completion
02
Recovery success
03
Human intervention rate
04
Validation pass rate
Boundaries & Guardrails
Validated state checkpoints
Checkpoint goals, inputs, intermediate results, and external-system state at consequential steps, then validate where execution should resume.
Isolated execution and safe recovery
Run tools in controlled workspaces or sandboxes, separating safely replayable actions from external effects requiring compensation.
Authorization, escalation, and stops
Set thresholds for low confidence, value judgments, and consequential actions so work pauses, requests approval, or stops when required.
Connected Technology
Every capability,working as one system.
Explore the technologies that provide enterprise context, task evaluation, and governance for long-running work.
01
Enterprise Product · GEA OS
Context System
Turn multimodal content, business state, and enterprise judgment into context for continuous agent action.
Learn more02Production Readiness
Agent Reliability & Evaluation
Make every run observable and measurable—and improve the next one.
Learn more03Production Readiness
Security & Governance
Keep every action within identity, access, and accountability boundaries.
Learn moreTechnical questions
Understand the mechanism, boundaries, and production requirements.
01
How is a Long-Horizon Agent Runtime different from a fixed workflow?
Fixed workflows suit tasks whose steps and branches can be defined in advance. A long-horizon runtime supports work whose path changes with new evidence, intermediate outcomes, and external events. It preserves goals and state, then adapts the next action within constraints instead of pre-writing every case.
02
Which tasks are a good fit for a Long-Horizon Agent Runtime?
It is best suited to work that runs over time, spans systems, requires repeated judgment, and changes direction as intermediate results arrive. When steps are fully deterministic, short-lived, and context does not evolve, conventional automation is usually simpler.
03
How do runtime state and the Context System differ?
Runtime state tracks where one task currently stands, including its goal, plan, dependencies, and intermediate outcomes. The Context System organizes enterprise knowledge, rules, relationships, and decision memory that can be reused across tasks. The runtime reads context to advance work, then writes validated outcomes back to complete the learning loop.
Ready when you are